Skip to main content

overloading assignment operator everywhere

Project description

assign-overload

This library makes it possible to overload assignment (=) operator. Inspired by assign. Along with other things, main difference from that library is assign calls the overloaded operator of the right hand side while this library calls of the left hand side.

Installation

pip install assign-overload

How To Use

First you need to overload the assignment operator using the function _assign_:

class T:        
    def _assign_(self, value, *annotation):
        print(f"called with {value}")
        return self

value is the value of right hand side. If the assignment is annotated, annotation will take a single argument carrying the annotation. Return value specifies the value of left hand side.

Next, in order to make this method automatically called you should call assign_overload.patch_and_reload_module():

import assign_overload

class T:        
    def _assign_(self, value, *annotation):
        print(f"called with {value}")
        return self


def main():
    a = T()
    a = 10 # a will keep holding the T object


if assign_overload.patch_and_reload_module():
    if __name__ == "__main__":
        main()

This function will find and modify the current module's source code, replacing right hand side of assignments with calls to _assign_, then execute the modified code. Once called, this function will introduce a new global variable to the current module: modified_source. This variable will be accessible while both executing the original module and modified module. It represents the source code of the modified module. Since module's __dict__ attribute is passed as the globals parameter of exec, names created in the modified module will be reflected on the original module along with their values, creating a reloading effect. Return value of this function specifies which module we are currently executing. True means modified module and False means original module. Any code outside the first if block will be executed twice. Codes before this function call will first be executed while executing the original module and second while executing the modified module. Codes after the first if block will first be executed while executing the modified module and second while executing the original module. This is especially bad because if a piece of code last executed while executing the original module, any function or class definition will have its original definition, not the modified definition they should have. Codes inside the first if block will only be executed while executing the modified module. You can wrap all your module code including functions and classes inside a single if block like this:

import assign_overload

if assign_overload.patch_and_reload_module():
    class T:        
        def _assign_(self, value, *annotation):
            print(f"called with {value}")
            return self


    def main():
        a = T()
        a = 10 # a will keep holding the T object


    if __name__ == "__main__":
        main()

But that doesn't look nice. Functions, classes and constant definitions are most probably okay to be executed twice but actual code should be executed once. Thus, the location in the first example is the best location for calling this function. This function should be called even if this module isn't the __main__ module because function and class definitions should be modified even if no real code is ought to be executed. This function should be called once. Consecutive calls doesn't modify and execute the source code again. Lastly, this function will introduce 2 other global varriables to the current module: patched and executing_patch. These variables are internally used by the library and they are documented here only to prevent the user from changing them.

Limitations

Unpacking during assignment and the walrus operator are not supported. If you attempt to call assign_overload.patch_and_reload_module() from a module using these features, you will face an error. Additionally, for classes, __slots__ mechanism is not supported. _assign_ function won't be called while assigning to a slot of an object even if the slot holds an object whose class defines _assign_.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

assign_overload-1.0.3.tar.gz (4.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

assign_overload-1.0.3-py2.py3-none-any.whl (5.0 kB view details)

Uploaded Python 2Python 3

File details

Details for the file assign_overload-1.0.3.tar.gz.

File metadata

  • Download URL: assign_overload-1.0.3.tar.gz
  • Upload date:
  • Size: 4.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.0

File hashes

Hashes for assign_overload-1.0.3.tar.gz
Algorithm Hash digest
SHA256 fe2e42f097415a19ed2977dbef320ea12eaa7086444159f55a608026f3f58b9f
MD5 09402de982bba00f7ac97c333f26a989
BLAKE2b-256 1e5322b07dbda48ee14c9197e35e534accb9c627e468dfd08645f0a688f5c14d

See more details on using hashes here.

File details

Details for the file assign_overload-1.0.3-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for assign_overload-1.0.3-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 b0b7db37345fd2606c5ce90fdc214ce846f00bcf95ccdc2db49eeb636968a83d
MD5 ee6176113b5e5e065741f4d268b412ea
BLAKE2b-256 f6eb51a8a2f897c556e74902affcc1fec0fdac0b12cb6a6b1e7d621216c2d662

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page